Richesson Submits NIH U18 Application

Kudos to Rachel Richesson, associate professor, and her entire team for the submission of their NIH U18 application entitled "Validation of a Metadata Framework for Clinical Pathway Knowledge Artifacts." This proposal requests funding for a two-year period with a start date of April 1, 2020. 

This research will test strategies for organizations to find appropriate clinical practice guidelines and decision support tools and integrate them into their electronic health record systems.

Health care organizations need to manage multiple clinical practice guidelines (CPGs) and underlying knowledge components, and to understand know where and how guideline-based clinical decision support (CDS) interventions can be integrated into EHR systems. To integrate CPGs into EHR systems, each knowledge component must contain enough information to retrieve and match it to the appropriate patient context. Descriptive metadata will be required to support the retrieval of CPGs and to design and implement context-specific CDS. However, as of yet, there are no standards for such metadata, so organizations and knowledge hosts develop their own. It is not clear which metadata are required for retrieval and application of guideline-driven context-specific CDS, what they will cost, or how reliable they are. To answer these questions, we will use a large collection of antenatal practice guidelines, developed by the American College of Obstetrics and Gynecology (ACOG), that are evidence-based and formatted as highly structured clinical pathways (n=50) and associated knowledge components (n>400), including patient features (clinical phenotypes), medical goals, explicit representations for clinical context and situational criteria, quality metrics, and decision logic. We propose to examine how metadata can enable the retrieval, feasibility assessment, and application for clinical pathways and associated CDS. We will apply different metadata to index this collection of ACOG knowledge objects and compare the burden and utility required to support clinical leaders in identifying appropriate CDS interventions and assessing their readiness for integration into current workflows. This is a demonstration project for metadata-assisted feasibility assessment for context-specific guideline-based CDS. The final metadata can be used to speed the planning, design, and implementation of CDS into health care organizations, ultimately supporting vision of scalable and widespread adoption of evidence-based guideline driven decision support.